• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.5
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• pp.163-171
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• 2013

This paper proposes an algorithm that seeks the optimal solution for an assignment problem through a simplified process. Generally it is Hungarian algorithm that is prevalently used to solve a given assignment problem. The proposed algorithm reduces 4 steps Hungarian algorithm into 2 steps. Firstly, the algorithm selects the minimum cost from a matrix and deletes the rest of the rows and columns. Secondly, it improves on the solution through reassignment process. For 27 balanced assignment problems and 7 unbalanced problems, the proposed algorithm has successfully yielded the optimal solution, which Genetic algorithm has failed. This algorithm is thus found to be an appropriate replacement of Hungarian algorithm.

• Nuclear Engineering and Technology
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• v.50 no.3
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• pp.425-431
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• 2018

Different methods of axial and tangential testing and various sample geometries were investigated, and new test geometries were designed to determine the ultimate tensile strength of zirconium cladding tubes. The finite element method was used to model the tensile tests, and the results of the simulations were evaluated. Axial and tangential tensile tests were performed on as-received and machined fuel cladding tube samples of both E110 and E110G Russian zirconium alloys at room temperature to compare their ultimate tensile strengths and the different sample preparation methods.

• Journal of the Korea Society of Computer and Information
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• v.20 no.8
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• pp.105-112
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• 2015

Generally, the optimal solution of assignment problem has been obtained by Hungarian algorithm with O($n^3$) time complexity. This paper proposes more simple algorithm with O($n^2$) time complexity than Hungarian algorithm. The proposed algorithm simply selects minimum cost in each row, and classified into set S, H, and T. Then, the minimum cost is moved from S to T and $S{\rightarrow}H$, $H{\rightarrow}T$. The proposed algorithm can be obtain the same optimal solution as well-known algorithms and improve the optimal solution of partial unbalanced assignment problems.

• Smart Media Journal
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• v.7 no.2
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• pp.9-14
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• 2018

The k-ary n-cube $Q^k_n$ is widely used in the design and implementation of parallel and distributed processing architectures. It consists of $k^n$ identical nodes, each node having degree 2n is connected through bidirectional, point-to-point communication channels to different neighbors. On $Q^k_n$ we would like to transmit packets from a source node to 2n destination nodes simultaneously along paths on this network, the $i^{th}$ packet will be transmitted along the $i^{th}$ path, where $0{\leq}i{\leq}2n-1$. In order for all packets to arrive at a destination node quickly and securely, we present an $O(n^3)$ routing algorithm on $Q^k_n$ for generating a set of one-to-many node-disjoint and nearly shortest paths, where each path is either shortest or nearly shortest and the total length of these paths is nearly minimum since the path is mainly determined by employing the Hungarian method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.3950-3964
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• 2017

With the increasing popularity of 3D technology such as 3D printing, 3D modeling, etc., there is a growing need to search for similar models on the internet. Matching non-rigid shapes has become an active research field in computer graphics. In this paper, we present an efficient and effective non-rigid model retrieval method based on topological structure and local volume. The integral geodesic distances are first calculated for each vertex on a mesh to construct the topological structure. Next, each node on the topological structure is assigned a local volume that is calculated using the shape diameter function (SDF). Finally, we utilize the Hungarian algorithm to measure similarity between two non-rigid models. Experimental results on the latest benchmark (SHREC' 15 Non-rigid 3D Shape Retrieval) demonstrate that our method works well compared to the state-of-the-art.

• Publications of The Korean Astronomical Society
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• v.32 no.1
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• pp.49-53
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• 2017

The point sources in the Bright Source Catalogue of the AKARI Far-Infrared Surveyor (FIS) were classified based on their FIR and mid-IR fluxes and colours into young stellar object (YSO) and extragalactic source types using a Quadratic Discriminant Analysis method (QDA) and Support Vector Machines (SVM). The reliability of the selection of YSO candidates is high, and the number of known YSO candidates were increased significantly, that we demonstrate in the case of the nearby open cluster IC348. Our results show that we can separate galactic and extragalactic AKARI point sources in the multidimensioal space of FIR fluxes and colours with high reliability, however, differentiating among the extragalactic sub-types needs further information.

• Journal for History of Mathematics
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• v.31 no.1
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• pp.37-51
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• 2018

In this paper, our main concern is the historical development of the Finsler geometry in Debrecen, Hungary initiated by L. Berwald. First we look into the research trend in Berwald's days affected by the $G{\ddot{o}}ttingen$ mathematicians from C. Gauss and downward. Then we study how he was motivated to concentrate on the then completely new research area, Finsler geometry. Finally we examine the course of establishing Hungarian Debrecen school of Finsler geometry via the scholars including O. Varga, A. $Rapcs{\acute{a}}k$, L. $Tam{\acute{a}}ssy$ all deeply affected by Berwald after his settlement in Debrecen, Hungary.

• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.897-904
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• 2013

The recursive circulant network G(N,d) can be widely used in the design and implementation of parallel processing architectures. It consists of N identical nodes, each node is connected through bidirectional, point-to-point communication channels to different neighbors by jumping $d^i$, where $0{\leq}i{\leq}{\lceil}{\log}_dN{\rceil}$ - 1. In this paper, we investigate the routing of a message on $G(2^m,4)$, a special kind of RCN, that is key to the performance of this network. On $G(2^m,4)$ we would like to transmit k packets from a source node to k destination nodes simultaneously along paths on this network, the $i^{th}$ packet will be transmitted along the $i^{th}$ path, where $1{\leq}k{\leq}m-1$, $0{{\leq}}i{{\leq}}m-1$. In order for all packets to arrive at a destination node quickly and securely, we present an $O(m^4)$ routing algorithm on $G(2^m,4)$ for generating a set of one-to-many node-disjoint and nearly shortest paths, where each path is either shortest or nearly shortest and the total length of these paths is nearly minimum since the path is mainly determined by employing the Hungarian method.

• Journal of Computing Science and Engineering
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• v.8 no.2
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• pp.87-93
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• 2014

Coronary artery disease (CAD) is currently a prevalent disease from which many people suffer. Early detection and treatment could reduce the risk of heart attack. Currently, the golden standard for the diagnosis of CAD is angiography, which is an invasive procedure. In this article, we propose an algorithm that uses data mining techniques, a fuzzy expert system, and the imperialist competitive algorithm (ICA), to make CAD diagnosis by a non-invasive procedure. The ICA is used to adjust the fuzzy membership functions. The proposed method has been evaluated with the Cleveland and Hungarian datasets. The advantage of this method, compared with others, is the interpretability. The accuracy of the proposed method is 94.92% by 11 rules, and the average length of 4. To compare the colonial competitive algorithm with other metaheuristic algorithms, the proposed method has been implemented with the particle swarm optimization (PSO) algorithm. The results indicate that the colonial competition algorithm is more efficient than the PSO algorithm.

• Smart Media Journal
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• v.7 no.4
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• pp.61-69
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• 2018

Multi-tracking of general objects and specific faces is an important topic in the field of computer vision applicable to many branches of industry such as biometrics, security, etc. The rapid development of deep neural networks has resulted in a dramatic improvement in face recognition and object detection problems, which helps improve the multiple-face tracking techniques exploiting the tracking-by-detection method. Our proposed method uses face detection trained with a head dataset to resolve the face deformation problem in the tracking process. Further, we use robust face features extracted from the deep face recognition network to match the tracklets with tracking faces using Hungarian matching method. We achieved promising results regarding the usage of deep face features and head detection in a face tracking benchmark.